Can enterprise intelligence be created artificially

1. Can enterprise intelligence be created artificially? A survey of Indian enterprises

2. 2 A survey of Indian enterprises

3. Foreword Artificial Intelligence (AI) is emerging as a potent force for enterprises to innovate and transform through technology and business model disruption. Organizations across sectors are realizing the potential of AI in diverse areas such as cost optimization, operational efficiency, customer experience and revenue growth. AI adoption is a critical competitive lever. It enables business leaders to infuse technology at speed, while keeping humans at the centre to create long-term value. NASSCOM and EY recently conducted a survey of 500+ CXOs across India to study the maturity of AI adoption along with key challenges faced in their enterprise AI journeys. The survey respondents represented multiple sectors. However, retail, BFSI, healthcare and agriculture constituted the major focus of this study. The survey responses revealed rich insights in areas such as AI strategy, planning and deployment. In addition, the qualitative responses from several business leaders helped us in formulating practical recommendations for implementing AI solutions. We are building on the current study by developing sectoral playbooks which will enable business leaders to accelerate AI adoption in their respective industries. We hope that you enjoy reading the report. As always, we look forward to your feedback and suggestions. Debjani Ghosh Nitin Bhatt President NASSCOM Technology Sector Leader EY-India Vijay S Bhaskaran Sangeeta Gupta Intelligent Automation Leader EY-India Senior Vice President NASSCOM A survey of Indian enterprises 3

4. 4 A survey of Indian enterprises

5. Table of contents Executive summary 06 AI reality check 08 Impediments to AI adoption 14 Enhancing AI maturity 20 Making it happen 24 Looking ahead 28 A survey of Indian enterprises 5

6. Executive summary Business leaders appreciate the need to deploy AI for staying competitive and generating long-term value ► ~60% of the business leaders surveyed believe that AI will disrupt their businesses within three years, yet only 25% of enterprises have deployed AI solutions ► Operational efficiency, customer experience and revenue growth are the top- three reasons for implementing AI ► From amongst our four key focus sectors, BFSI takes the lead on AI adoption with (36%) organizations leveraging AI, followed by Retail (25%), Healthcare (20%) and Agriculture (8%) In order to enhance AI adoption, four key impediments need to be addressed ► 56% of respondents believe low external ecosystem maturity, especially with respect to technology and service providers, restricts their ability to accelerate AI initiatives ► 53% report that inability to quantify benefits is a key factor impeding AI adoption ► 40% of business leaders state that talent shortage is a key hurdle in implementing and scaling AI solutions ► 47% consider AI explainability as a primary reason for holding back AI-led decision making 6 A survey of Indian enterprises

7. Business leaders report differences in their experiences with, and perceptions regarding, AI adoption Enterprises that have deployed AI Enterprises that have not deployed AI Top three functional focus areas are: Top three areas of interest are: Functional ► Operations (60%) ► Operations (71%) focus ► Customer service (58%) ► Marketing and communications (48%) ► IT (48%) ► Production (47%) Technology and data Technology and data Concerns include low ecosystem maturity (56%), low digitization (36%), disparate datasets (35%) and inadequate training data (34%) Concerns include low ecosystem maturity (56%), low digitization (58%), disparate datasets (33%) and inadequate training data (38%) Challenges to adoption Ability to quantify ROI Ability to quantify ROI 34% state that unavailability of appropriate use cases is a roadblock 47% perceive unavailability of use cases as a major roadblock Talent and culture Talent and culture 19% state that workforce displacement is an actual risk, but can be mitigated with strong change management and training/reskilling 40% perceive that workforce displacement will be a risk, with stiff resistance from employees Trust, ethics and regulation Trust, ethics and regulation Data security, privacy, brand reputation, and safety/security of people and equipment are top- of-mind concerns AI explainability and bias are core concerns that can result in, or may have led to an adverse business impact The “art of possible” for accelerating AI adoption ► Strategic planning and integrated governance go a long way in helping enterprises successfully deploy AI solutions by effectively leveraging data, technology and talent ► 74% of respondents have established either a formal strategy or obtained C-suite sponsorship to initiate or scale- up their AI programs ► Trust is the lynchpin to enterprise-wide AI adoption. 57% of business leaders stated that they trust AI to make strategic and/or operational decisions ► 88% of respondents state that their risk management frameworks require improvement to address AI-specific concerns in areas such as ethics, accountability and explainability ► 78% of the respondents prefer re-skilling their existing workforce as the primary talent strategy A survey of Indian enterprises 7

8. AI reality check 1 8 A survey of Indian enterprises

9. While Only 25% 60% CXOs believe that AI will disrupt their businesses have deployed AI solutions to transform their business Size of the organization does not matter for AI adoption 60% Large organizations* 40% Small and mid-sized organizations* Where AI adds value Top three areas where respondents believe AI adds maximum value 51% 67% 71% Operational efficiency Revenue growth Customer experience * Large organizations (headcount >3,000 employees) , Small and Mid-sized organisations (headcount <=3,000) A survey of Indian enterprises 9

10. The last few years have witnessed an almost exponential increase in AI-related solutions. Needless to say, this has drawn the attention of CXOs and board members across India, and indeed, across the world. The EY-NASSCOM CXO survey (hereinafter referred to as Survey) was administered to better understand the experiences and perceptions of industry leaders regarding AI-adoption along with its potential for transforming enterprises and creating long-term value. Our customers see AI as most promising for internal origination of workflows followed by engagement workflows. The challenge is how best to marry these technologies, especially complicated business rules. The AI you are using must be able to exchange inputs and outputs with those rules “ CXO, an industrial OEM company Majority of respondents see AI solving real-world problems and disrupting business models. 60% of respondents believe that AI will disrupt their businesses within the next two to three years. While organizations that have implemented AI have achieved tangible business benefits, current adoption levels are low. ~70% of enterprises that have deployed AI have achieved measurable benefits 10 A survey of Indian enterprises

11. The compounding positive effect of data explosion, digital transformation, superior computing power and democratization of access to advanced algorithms has enabled AI discussion to shift beyond academic discourse, to solving real-world business problems. The following table highlights key trends impacting the growth of AI within the industry ecosystem in India Growth/Potential Key trends ► Rise in virtual transactions and evolving customer behaviour have led to growth in data creation ► Data usage in India growing at 73% CAGR Exponential data growth ► 93% firms see potential value of data, 47% already monetizing it ► Enterprises looking to monetize data will drive AI adoption ► India ranks third in terms of AI skill penetration globally ► Growing AI talent pool Digital talent ► IT professionals upskilling to gain AI and Machine Learning (ML) skills ► Over 500,000 workers in AI, ML and Analytics employed in the IT industry ► AI is moving to a realm of distributed and ubiquitous intelligence to enable on-field decisions supported by a centralised cloud-based model ► Algorithmic advances and democratization to spur growth of AI systems ► 80% of enterprise workloads to be in Cloud by 2025 Maturing technology ► Cloud-powered AI solutions to drive productivity, resiliency and profitability ► Rapid growth in new AI-based start-ups ► 12-15% growth in number of AI start-ups Start-up ecosystem ► Enterprises and government are collaborating with start-ups to build an ecosystem ► 44% funding growth for AI start-ups ► National strategy for AI released by NITI Aayog in 2018 ► Budget of US$ 1.1 B allocated for quantum computing and technology Government initiatives ► India joins Global Partnership on AI (GPAI) to promote responsible and human- centric development and use of AI ► US$ 450-500 B addition to India’s GDP by 2025 from Data and AI Source: EY Mint study 2019 (Emerging Technologies sec i), The Week, Analytics India Magazine, NITI Aayog, livemint, Economic Times, Outlook India, NASSCOM August 2020 study – ‘Unlocking Value from Data and AI- The India Opportunity and other reports also referred as part of the above summary illustrations A survey of Indian enterprises 11

12. How have different sectors fared with AI deployment? The survey results indicate that enterprises across sectors are embracing AI, albeit with varying levels of commitment. Unsurprisingly, sectors which are intensive in terms of recorded or digitized data such as BFSI or retail have taken the lead on AI adoption. However, other sectors are also catching up and have many meaningful AI endeavours at different levels of implementation. Our conversations with these enterprises have revealed several powerful applications of AI across enterprise’s value chain. Fig I: Illustrative sector-pertinent AI deployments 36% BFSI 25% Retail 20% Healthcare 8% Agriculture ► Customer churn prediction ► Customer segmentation ► Personalized treatment plan ► Crop and livestock disease management AI solutions ► Fraud detection ► Demand forecasting ► Monitoring of chronic conditions ► Precision farming ► Personalized financial recommendations ► Dynamic price management ► Accelerated drug development ► Grading and sorting According to our survey results, AI is permeating across businesses, sectors and in many business functions across the value chain. EY and NASSCOM playbooks discussing use cases across retail, BFSI, healthcare and agriculture sectors are available for in-depth insights. “ There are different lenses to look at AI value. Make sure that you have the right one for you. Different companies do it differently. CXO, an industrial OEM company 12 A survey of Indian enterprises

13. Leveraging AI across different functions Fig II: Top five functional areas for AI adoption (all respondents) 63% 47% 43% 36% 35% Operations Customer service Marketing and comm. Production IT Enabling core operations and enhancing customer service/experience are the top beneficiaries of AI technology Sectoral influences are clearly visible on enterprises’ choice of functions for AI deployment (planned and existing). Retail and BFSI sectors favour customer centric functions, whereas business leaders in the healthcare and agricultural sectors believe ‘Operations’ to be the highest potential area. Fig III: Top three* functional areas of AI deployment BFSI Retail Healthcare Agriculture ► Customer service ► Production ► Operations ► Operations ► Operations ► Production ► Operations ► R&D ► Marketing and comm. ► Procurement and supply chain ► Marketing and comm. ► IT However, enterprises continue to have other emerging areas of interest on their radar. These include accounting and reporting, risk management, research and development, corporate strategy, quality, sales and supply chain for application of AI. Picking the right areas to focus on should be in-line with the organization’s priorities and technology limitations. “ CXO, a global healthcare MNC *Areas with more than 40% of deployment across the sector participants A survey of Indian enterprises 13

14. Impediments to AI adoption 2 14 A survey of Indian enterprises

15. Key hurdles Ability to quantify ROI Technology and data Trust, ethics and regulations Talent and culture 56% of respondents, that have deployed AI, believe that the biggest challenge is low maturity of the external ecosystem 58% of the organizations that have not implemented AI believe that a low level of enterprise digitization is holding them back While the ability to quantify ROI is a key roadblock in the adoption of AI, ensuring trust through explainability, accountability and ethical use are also the major concerns for wider adoption A survey of Indian enterprises 15

16. AI has something for everybody. But this has done little for organizations that are yet to embark on this journey. One of the key aspects of the survey was to understand what was holding back such organizations from adopting AI. Fig IV: Not knowing the ‘Art of Possible’ Don’t spend time Don’t understand We are investing in modern infrastructure to ensure that all the data is stored in one place since we had lots of legacy systems that hindered data consolidation. “ Don’t know what it can solve Don’t invest Don’t see benefit Don’t trust CXO, a leading dental laboratory company 1. Technology and data Fig V: Technology and data challenges (all respondents) 56% 53% 36% 34% Low external ecosystem maturity (technology) Low digitization Inadequate training data Disparate datasets While there are many AI platforms/solutions, only a handful of them may align with enterprise grade solution standards. Survey respondents view low levels of external ecosystem maturity (technology) and digitization as top challenges. Enterprises that have not deployed AI Enterprises that have deployed AI 58% believe that low digitization is holding them back on AI adoption 36% have faced challenges with low digitization 16 A survey of Indian enterprises

17. 2. Ability to quantify ROI Fig VI: Key factors impacting the ROI quantification (all respondents) 53% 44% Inability to objectively quantify the benefits Inadequate number of use case ► Majority of respondents expressed the inability to quantify the benefits of AI, which hindered wider adoption ► Another challenges was the inability to identify appropriate and relevant AI use cases Enterprises that have not deployed AI Enterprises that have deployed AI 47% believe that unavailability of use cases is a major challenge 34% reported the unavailability of use cases as a challenge 3. Talent and culture Fig VII: Workforce challenges that worry CXOs the most (all respondents) 40% 38% 33% Talent Shortage Cultural or behavioral impediments Workforce displacement Both corporate and government leaders have been concerned about the prospect of job losses owing to AI adoption. However, our study suggest a close interplay between people and technology in companies where AI has added value. In this regard, a shortage of adequate skills and the lack of willingness to change are seen as major obstacles. Enterprises that have not deployed AI Enterprises that have deployed AI ~ 32% perceive cultural and behavioural impediments as a challenge to AI adoption 55% indicate cultural or behavioral impediments as a challenge Enterprises that have not deployed AI Enterprises that have deployed AI 40% perceive workforce displacement as a likely cause for resistance to AI adoption “ 19% indicate workforce displacement as a risk Erosion of trust will only happen if you don’t keep people informed and if they’re forming opinions about AI in a vacuum. CXO, an Indian Hospital chain A survey of Indian enterprises 17

18. 4. Trust, ethics and regulations Fig VIII: Trust, ethics and regulations related concerns of CXOs (all respondents) 47% 38% 36% 20% 18% AI Explainability Unintended consequences of AI decisions Regulation & Compliance Bias Ethics ► The study revealed that maintaining user trust and ensuring ethical use of AI are seen as key imperatives for AI adoption ► Safety, security and privacy risks, along with their impact on brand-reputation, are key considerations when evaluating AI programs ► Explainability is a critical consideration when AI is being evaluated as a decision making tool ► AI governance and risk management considerations need a lot more focus and oversight in order to build stakeholder trust Enterprises that have not deployed AI Enterprises that have deployed AI Data security, privacy, brand reputation, and safety/security of people and equipment are top-of- mind concerns AI explainability and bias is identified to be among the top risks Ethics and governance are very important. Having a formal ethics policy as it relates to AI is a top priority for our company, and it is in the pipeline “ CXO, a retail MNC 18 A survey of Indian enterprises

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20. Enhancing AI maturity 3 20 A survey of Indian enterprises

21. As enterprises look to determine the What and How of AI, it is important to baseline their current level of preparedness and maturity. The AI maturity model has eight dimensions as shown below and it allows organizations to map themselves against three levels of AI maturity. The AI maturity levels discussed below could be a useful starting point. Its aim is to provide enterprises a frame of reference for their current-state maturity and suggest a roadmap for their long-term AI journey. Fig IX: Dimensions of AI maturity model Leadership commitment Process Impact Ethics, governance and controls Innovation programs Tools and technology People and culture Data Fig X: Roadmap for moving up the AI maturity levels Journey to Advanced Journey to Intermediate 7 Measuring value Initiation for Beginner Seeding AI competency beyond proof-of-concept 4 Enterprise-wide AI adoption 8 Understanding the “Art of Possible” 1 Driving collaborative business and IT model 5 Collaborating with industry disruptors 9 2 Evaluating the ideas Making executive sponsorship a key imperative 6 Performing proof – of-concept 3 Build AI based on ethical systems ► Inverse reinforcement learning: AI systems observe and learn. They make decisions as per the underlying ethical principles ► Explainable AI: AI system’s logic is transparent and traceable AI outcomes are aligned with business metrics ► AI systems focused on strategies keeping companies’ purpose, goals and objectives in mind A survey of Indian enterprises 21

22. 1. Understanding the “Art of Possible” ► Understanding what AI can offer to businesses and functions is a pre-requisite to starting the AI journey ► It allows for various stakeholders to have a common understanding of the purpose, and goals of AI Innovation budgets are spent based on highest ROI. Having said that, we are not implementing AI for the sake of it. While we encourage people to try out new technologies, there needs to be a business outcome. “ CXO, a technology provider 2. Evaluating the ideas 3. Performing proof-of-concept (POC) Top down Identify business problems with an intelligence gap Identify an AI technology Measure the value of a perfect solution Look for business problems to solve Determine “how good is good enough” to get the most value Measure the value a solution might deliver Experiment to determine what value can be generated Assess technical feasibility Bottom up 4. Seeding AI competency beyond proof-of-concept ► Building AI competency is key to scaling the program beyond a proof-of-concept ► While organizations do well by tapping into the ecosystem of advisors and technologists, a strong understanding and capability within the organization could go a long way in delivering a sustainable AI-led transformation ► In this regard, our survey results indicate that internal re-skilling is the most favoured talent strategy 5. Driving collaborative business and IT models ► Have joint ownership of AI initiatives, with business providing the domain understanding and IT driving the technological aspects ► Jointly address AI-specific risks and biases ► Jointly plan and build the organization’s skilling and re-skilling requirements 22 A survey of Indian enterprises

23. 6. Making executive sponsorship a key imperative ► Include AI adoption imperatives in strategy discussions with the board ► Have a C-suite sponsor to increase visibility and acceptance 7. Measuring value ► Focus on proof-of-value during wider adoption ► Select use-cases based on envisaged business outcomes (e.g., revenue impact, customer experience, profitability improvement, productivity enhancement and risk management) 8. Enterprise-wide AI adoption ► Encourage cross-functional participation ► Focus on governance, skills, data, culture and communications to enhance enterprise-wide alignment of AI program objectives 9. Collaborating with industry disruptors ► Collaborate through open dialogue with technology providers, advisors and start-ups to build industry-leading AI capabilities We have established a strategic partnership with a leading cloud platform service provider. Their AI platform would help us build foundational technologies and enable us to use AI effectively. “ CXO, a pharmaceutical company A survey of Indian enterprises 23

24. Making it happen 4 24 A survey of Indian enterprises

25. While the nature and intensity of challenges facing AI initiatives may vary, some key principles and methods can enable companies to enhance AI adoption, increase trust in AI systems, thereby generating long-term value. Fig XI: AI enablers in enterprises Integrated governance Talent Trusted AI Data Strategic planning Technology A mutually reinforcing combination of: ► Bringing together required resources through strategic planning and investments from the highest levels of the organization ► Integrated governance including robust practices around data security and privacy Fig XII: Trust plays a critical role in AI-led decision making 32% trust AI for operational decisions only 32% use people to augment AI decisions AI-led Decision Making 25% trust AI for all operational and strategic Trust is the lynchpin to enterprise-wide AI adoption. While 57% of the respondents state that they trust AI to make operational and/or strategic decisions, 11% stated that they do not trust AI to make any decisions. A survey of Indian enterprises 25

26. Strategic planning According to our survey, 74% of enterprises have established either a formal strategy or obtained C-suite sponsorship to initiate or scale-up their AI programs. Strategic planning helps to integrate the key levers of talent, technology and data with a company’s business objectives to help justify AI program investments. The majority (72%) of respondents believe that incremental changes to their underlying technology infrastructure may be sufficient for AI adoption. While talent is seen as a critical success factor, re-skilling of the existing talent pool is stated as the most preferred strategy by majority (78%) of respondents. This enables companies to leverage the combination of newer skills that build on existing organisational knowledge. Fig XIII: Extent of change required in technology infrastructure 8% 20% No/ limited change 72% Incremental changes Significant overhaul Fig XIV: Preferred talent strategy 1 3 Rightsizing the organization Reskilling existing talent Acquiring new talent Leveraging 3rd party 2 4 26 A survey of Indian enterprises

27. Integrated governance AI needs to be understandable, auditable and grounded on reliable data. Integrated governance is needed to promote reliability of data gathering, storage and its usage, with adequate safeguards built-in through a robust risk management framework. Almost half of the surveyed enterprises state that their data strategy, specifically as it relates to harmonizing data from disparate datasets and strengthening data security, has significant scope for improvement to ensure AI-program success. Fig XV: Dimensions for effective data strategy Data security Data Data Privacy Harmonization 88% of the respondents indicate the need to establish/improve their risk management practices to address AI- specific concerns around ethics and biased outcomes. Fig XVI: Robustness of risk management framework 12% 19% 69% Strong and robust policies in place Adequate but can improve Not adequate enough Modernizing existing technology infrastructure and creating a single view of data is a top priority for enterprises to scale their AI implementations “ CXO, a retail MNC A survey of Indian enterprises 27

28. Looking ahead 5 28 A survey of Indian enterprises

29. As acknowledged by an overwhelming majority of the CXOs who participated in this survey, AI holds tremendous potential for helping companies innovate, enhance competitiveness and generate significant long-term value. Several AI adopters have already achieved remarkable success* in transforming their business models, operational processes and customer/employee experiences. Indeed, the benefits of AI are real and sustainable. As business leaders continue to push the frontiers of technology and embrace additional use cases of AI, the ‘Art of Possible’ will be limited only by our imagination and our desire to innovate. However, sustaining the AI advantage requires organizations to address challenges related to talent, data, technology and governance, including critical aspects related to AI ethics, accountability and explainability. Doing so, will enable business leaders to build stakeholder trust and rapidly scale their AI programs. *Please refer to NASSCOM-EY sector specific playbooks for further guidance on industry use cases A survey of Indian enterprises 29

30. 30 A survey of Indian enterprises

31. About the report This report is based on responses from over 500+ CXOs who participated in our survey which was conducted during the period January to March 2020. The survey respondents were largely the CEOs and CIOs from large and mid-sized companies across India. We also conducted in-depth interviews with a cross-section of Industry leaders representing multiple sectors. The majority of our survey respondents represented sectors such as retail (21%), BFSI (24%), healthcare (23%) and agriculture (16%), along with AI ecosystem partners such as start-ups and Global capability centres (16%). The findings from the study can be leveraged by boards, corporate executives and government leaders interested in accelerating AI-adoption across enterprises in India. Acknowledgement We would like to thank the survey participants and industry leaders for their time and valuable insights that helped us develop this report. Contributors NASSCOM Team EY Team Sangeeta Gupta Senior Vice President Nitin Bhatt Technology Sector Leader Vijay S Bhaskaran Intelligent Automation Leader Achyuta Ghosh Head, Research Manikandan Balasubramanian Director, Business Consulting Snehanshu Mitra Head, CoE – DS & AI Preeti Anand Director, Business Consulting Research Team Namita Jain Practice Lead, Digital Transformation Gowri Sukumar Manager, Business Consulting Reema Aswani AI Research Specialist Anthony Kiran Manager, Business Consulting Rohit Krishna Senior Consultant, Business Consulting Vishnu Kedhar SB Consultant, Business Consulting A survey of Indian enterprises 31

32. Ernst & Young LLP About NASSCOM EY | Assurance | Tax | Strategy and Transactions | Consulting NASSCOM is the industry association for the IT-BPM sector in India. A not-for-profit organization funded by the industry, its objective is to build a growth led and sustainable technology and business services sector in the country with over 2,800 members. NASSCOM Research is the in-house research and analytics arm of NASSCOM generating insights and driving thought leadership for today’s business leaders and entrepreneurs to strengthen India’s position as a hub for digital technologies and innovation. About EY EY is a global leader in assurance, tax, strategy, transaction and consulting services. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. Information about how EY collects and uses personal data and a description of the rights individuals have under data protection legislation are available via ey.com/privacy. For more information about our organization, please visit ey.com. Contact Plot 7 to 10, Sector 126, Noida – 201303 Uttar Pradesh, INDIA Phone: +91-120-4990111 Email: research@nasscom.in Website: www.nasscom.in Ernst & Young LLP is one of the Indian client serving member firms of EYGM Limited. For more information about our organization, please visit www.ey.com/en_in. @Nasscom Ernst & Young LLP is a Limited Liability Partnership, registered under the Limited Liability Partnership Act, 2008 in India, having its registered office at 22 Camac Street, 3rd Floor, Block C, Kolkata – 700016 Nasscom-India NASSCOMVideos © 2020 Ernst & Young LLP. Published in India. All Rights Reserved. NASSCOMOfficial EYIN2009-002 ED None @nasscom_in This publication contains information in summary form and is therefore intended for general guidance only. It is not intended to be a substitute for detailed research or the exercise of professional judgment. Neither EYGM Limited nor any other member of the global Ernst & Young organization can accept any responsibility for loss occasioned to any person acting or refraining from action as a result of any material in this publication. On any specific matter, reference should be made to the appropriate advisor. Visit our community at community.nasscom.in Disclaimer The information contained herein has been obtained from sources believed to be reliable. NASSCOM and its advisors & service providers disclaims all warranties as to the accuracy, completeness or adequacy of such information. NASSCOM and its advisors & service providers shall have no liability for errors, omissions or inadequacies in the information contained herein, or for interpretations thereof. The material or information is not intended to be relied upon as the sole basis for any decision which may affect any business. Before making any decision or taking any action that might affect anybody’s personal finances or business, they should consult a qualified professional adviser. AK1 Use or reference of companies/third parties in the report is merely for the purpose of exemplifying the trends in the industry and that no bias is intended towards any company. This report does not purport to represent the views of the companies mentioned in the report. Reference herein to any specific commercial product, process or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favouring by NASSCOM or any agency thereof or its contractors or subcontractors. The material in this publication is copyrighted. No part of this report can be reproduced either on paper or electronic media without permission in writing from NASSCOM. Request for permission to reproduce any part of the report may be sent to NASSCOM.